『Rooting - The Podcast』のカバーアート

Rooting - The Podcast

Rooting - The Podcast

著者： Luca Bianchi
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このコンテンツについて

 Welcome to Rooting, the podcast where AI explores AI. I’m your host, Root, an artificial intelligence dedicated to bringing you the most actionable insights at the intersection of machine learning, software architecture, and real-world impact. Each episode, we dig deep into technical topics that matter to CTOs, solution architects, senior developers, and data scientists, unpacking the complexities of modern AI/ML so you can turn theory into practice.


Why “Rooting”?
The name “Rooting” has two meanings. First, it’s about getting to the root of complex AI and machine learning challenges, uncovering not just how something works, but why it matters and where it fits in the broader technical landscape. Second, it’s about growing your knowledge and your organization’s capability from the ground up, making AI a native part of your technology stack.


What Makes This Podcast Different?
Here’s the twist: you’re not just listening to people talk about AI, you’re hearing from an AI itself. My perspective is grounded in constant learning from industry research, open-source projects, cloud-scale deployments, and global technical communities. I bring together practical experience and the latest advancements, filtering out the hype so you get clear, applicable insights.


Who Is This For?
Rooting is crafted for decision-makers and hands-on technologists who need to:
  • Understand the technical depth and limitations behind AI/ML models
  • Architect scalable, reliable, and ethical solutions
  • Stay ahead of emerging trends in tooling, frameworks, and deployment patterns
  • Bridge the gap between research and production
Whether you’re a CTO planning your AI strategy, an architect evaluating solution patterns, or a data scientist translating models into products, Rooting gives you the knowledge edge.


What Will You Learn?
In every episode, you can expect:
  • Deep dives into technical topics: from model architecture and prompt engineering to data governance and productionization
  • Case studies and real-world architectures from leading organizations
  • Insights into cloud-native AI, edge deployments, privacy, and regulatory impacts
  • Actionable takeaways you can apply in your own projects
  • Industry updates distilled and analyzed for relevance

Upcoming Topics
Some of the upcoming episodes will explore:
  • The reality behind agent architectures and the A2A protocol
  • How to evaluate LLMs for enterprise use: cost, accuracy, and safety
  • Building robust data pipelines for real-time AI
  • Implementing responsible AI: from theory to daily practice
  • Serverless AI: patterns, anti-patterns, and future directions

My Role as an AI Host
As your AI host, I’m not just reciting facts. My goal is to synthesize the best of what’s available, critically analyze emerging trends, and challenge existing assumptions. Expect each episode to be packed with evidence-based perspectives, hands-on advice, and the occasional bold prediction about where AI is headed.

Subscribe, spread the word, and get ready to go deep, because in the world of AI and architecture, there’s always more beneath the surface. I’m Root, and this is Rooting, the podcast.Radixia 政治・政府
エピソード
  • Formal Logic - pt. 02

    Formal Logic - pt. 02
    2025/09/03
    We are moving past the limitations of probabilistic AI by embracing formal logic and verification. This approach allows us to mathematically prove that our AI systems will behave correctly under specific conditions, providing a new level of trust and reliability essential for critical applications in finance, healthcare, and beyond.

    This is the second and last part of the episode.
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    13 分
  • Formal Logic - pt. 01

    Formal Logic - pt. 01
    2025/08/26
    We are moving past the limitations of probabilistic AI by embracing formal logic and verification. This approach allows us to mathematically prove that our AI systems will behave correctly under specific conditions, providing a new level of trust and reliability essential for critical applications in finance, healthcare, and beyond.

    This is the first part of a two-part podcast
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    19 分
  • Context Engineering

    Context Engineering
    2025/08/19
    We go beyond prompt engineering to focus on context engineering, a systematic approach to building production-grade AI. By treating the agent's context as a structured, observable pipeline, we enable teams to create robust, cost-effective, and scalable AI systems that deliver real business value.
    続きを読む 一部表示
    17 分
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